#Parameters (global variables):
#    ranges: list of RangeSelection havinf args = (step_size, step_time, iterations)
#    pass_energy
#    save_scienta_image
#
#    skip_iteration: if set to 1 then skips after end of current iteration
from ch.psi.pshell.data.LayoutDefault import ATTR_WRITABLE_DIMENSION as ATTR_WRITABLE_DIMENSION

cur_range = 0
cur_iteration = 0

if Scienta.acquisitionMode != Scienta.AcquisitionMode.Swept:
    Scienta.acquisitionMode = Scienta.AcquisitionMode.Swept
ret=[]


set_exec_pars(open = True)

#Global arguments
Scienta.passEnergy = pass_energy

names=[]
names.append("Online Spectrum")
for i in range(len(ranges)):       
    names.append(str(ranges[i]))
plots = plot(None, names)
spectrum_series = plots[0].getSeries(0)
def plot_cur_spectrum():
    global spectrum_series
    try:
      while get_context().state.running:
        y = Scienta.spectrum.take(100)
        x = Scienta.spectrumX
        spectrum_series.setData(x, y)        
        time.sleep(1.0)
    finally:
        print "Stopping spectrum plotting"        
task = None

try:
    for cur_range in range(len(ranges)): 
        cur_iteration = 0 
        skip_iteration = False        
        Scienta.lowEnergy.write(ranges[cur_range].min)
        Scienta.highEnergy.write(ranges[cur_range].max)
        Scienta.update()

        vars = ranges[cur_range].vars
        Scienta.stepTime.write(vars[0])
        Scienta.stepSize.write(vars[1])
        Scienta.setIterations(1)

        set_adc_averaging()

        #iterations done in script
        xdata = None
        ydata = None
        image_data = None
        task = fork(plot_cur_spectrum)

        path="scan" + str(cur_range+1) + "/"
        for cur_iteration in range(vars[2]):   
            plots[cur_range+1].setTitle(str(ranges[cur_range]) + " - iteration " + str(cur_iteration+1))
            while True:
                wait_beam()
                trig_scienta()
                spectrum_array = Scienta.spectrum.read()                
                if beam_ok:
                    break
            if ydata is None:
                ydata = spectrum_array
            else:
                for k in range (len(spectrum_array)):
                    ydata[k] = ydata[k] + spectrum_array[k]
            if xdata is None:
                xdata = Scienta.spectrumX
            plots[cur_range+1].getSeries(0).setData(xdata, ydata)
            if save_scienta_image:
                image_array = Scienta.dataMatrix.read()
                if image_data is None:
                    image_data = image_array
                else:
                    for k in range (len(image_data)):
                        for j in range (len(image_data[0])):
                            image_data[k][j] = image_data[k][j] + image_array[k][j]
            if skip_iteration: 
                break            
            save_dataset(path + "ScientaSpectrum", ydata)            
            set_attribute(path, "Iterations",cur_iteration+1)
            if save_scienta_image:
                save_dataset(path + "ScientaImage", image_data)
            if cur_iteration==0:
                save_dataset(path + "ScientaChannels", xdata)
                set_attribute(path + "ScientaChannels", ATTR_WRITABLE_DIMENSION, 1)
                set_attribute(path, "Range Low", ranges[cur_range].min)
                set_attribute(path, "Range High", ranges[cur_range].max)
                set_attribute(path, "Step Time",vars[0])
                set_attribute(path, "Step Size",vars[1])
                set_attribute(path, "Pass Energy",pass_energy)
                set_attribute(path, "Readables", ["ScientaSpectrum","ScientaImage"] if save_scienta_image else ["ScientaSpectrum",])
                set_attribute(path, "Writables", ["ScientaChannels",])
                create_diag_datasets(path)
                append_diag_datasets(path)                

        plots[cur_range+1].setTitle(str(ranges[cur_range]))
        ret.append((xdata, ydata))

        """
        save_dataset(path + "ScientaSpectrum", ydata)
        save_dataset(path + "ScientaChannels", xdata)
        if save_scienta_image:
            save_dataset(path + "ScientaImage", image_data)
        set_attribute(path + "ScientaChannels", ATTR_WRITABLE_DIMENSION, 1)
        set_attribute(path, "Range Low", ranges[cur_range].min)
        set_attribute(path, "Range High", ranges[cur_range].max)
        set_attribute(path, "Step Time",vars[0])
        set_attribute(path, "Step Size",vars[1])
        set_attribute(path, "Pass Energy",pass_energy)
        set_attribute(path, "Iterations",cur_iteration+1)
        set_attribute(path, "Readables", ["ScientaSpectrum",])
        set_attribute(path, "Writables", ["ScientaChannels",])
        create_diag_datasets(path)
        append_diag_datasets(path)
        """


finally:
    cur_range = -1
    if not Scienta.isReady():
        Scienta.stop()
    Scienta.update()
    task[0].cancel(True)
    if ENDSCAN:
        after_scan()    
    
set_return(to_array(ret,'o'))